utils/wandb_logging PEP8 reformat (#2755)

* wandb_logging PEP8 reformat

* Update wandb_utils.py

utils/wandb_logging/log_dataset.py

@@ -1,10 +1,8 @@
 import argparse
-from pathlib import Path
 
 import yaml
 
 from wandb_utils import WandbLogger
-from utils.datasets import LoadImagesAndLabels
 
 WANDB_ARTIFACT_PREFIX = 'wandb-artifact://'
 
@@ -21,6 +19,6 @@ if __name__ == '__main__':
     parser.add_argument('--single-cls', action='store_true', help='train as single-class dataset')
     parser.add_argument('--project', type=str, default='YOLOv5', help='name of W&B Project')
     opt = parser.parse_args()
-    opt.resume = False # Explicitly disallow resume check for dataset upload Job
+    opt.resume = False  # Explicitly disallow resume check for dataset upload job
 
     create_dataset_artifact(opt)

utils/wandb_logging/wandb_utils.py

@@ -1,12 +1,9 @@
-import argparse
 import json
-import os
-import shutil
 import sys
+from pathlib import Path
+
 import torch
 import yaml
-from datetime import datetime
-from pathlib import Path
 from tqdm import tqdm
 
 sys.path.append(str(Path(__file__).parent.parent.parent))  # add utils/ to path
@@ -33,6 +30,7 @@ def check_wandb_config_file(data_config_file):
         return wandb_config
     return data_config_file
 
+
 def get_run_info(run_path):
     run_path = Path(remove_prefix(run_path, WANDB_ARTIFACT_PREFIX))
     run_id = run_path.stem
@@ -40,6 +38,7 @@ def get_run_info(run_path):
     model_artifact_name = 'run_' + run_id + '_model'
     return run_id, project, model_artifact_name
 
+
 def check_wandb_resume(opt):
     process_wandb_config_ddp_mode(opt) if opt.global_rank not in [-1, 0] else None
     if isinstance(opt.resume, str):
@@ -53,6 +52,7 @@ def check_wandb_resume(opt):
             return True
     return None
 
+
 def process_wandb_config_ddp_mode(opt):
     with open(opt.data) as f:
         data_dict = yaml.load(f, Loader=yaml.SafeLoader)  # data dict
@@ -77,7 +77,6 @@ def process_wandb_config_ddp_mode(opt):
         opt.data = ddp_data_path
 
 
-
 class WandbLogger():
     def __init__(self, opt, name, run_id, data_dict, job_type='Training'):
         # Pre-training routine --
@@ -110,8 +109,8 @@ class WandbLogger():
             if self.job_type == 'Dataset Creation':
                 self.data_dict = self.check_and_upload_dataset(opt)
         else:
-            print(f"{colorstr('wandb: ')}Install Weights & Biases for YOLOv5 logging with 'pip install wandb' (recommended)")
-
+            prefix = colorstr('wandb: ')
+            print(f"{prefix}Install Weights & Biases for YOLOv5 logging with 'pip install wandb' (recommended)")
 
     def check_and_upload_dataset(self, opt):
         assert wandb, 'Install wandb to upload dataset'